Presenting Effective way to Model Strategic Debt Recovery in World Trade : A Strategic Management Approach

Authors

  • Pedram Gharaei  KMD Holding, Tehran, Iran

Keywords:

Financial Debt, Financial Ratio, Efficiency, Data Envelopment Analysis, Logistic Regression

Abstract

The current system of global trade, which has become the World Trade Organization (WTO), has been struggling to balance business ever since. The research has been designed to provide an appropriate model for predicting financial compensation for insolvent countries of the WTO member country. Therefore, along with important financial ratios for predicting financial compensation, the efficiency of countries that can add accuracy and model prediction power is used as a predictor variable. First, the data envelopment analysis method can be used to calculate the efficiency index of insolvent member countries of the WTO, and then the result of the efficiency indicator can be used as a variable for predicting financial debt compensation along with other financial ratios. In the proposed method, data envelopment analysis is used as a means to evaluate input-output efficiency of each country. Using statistical tests, the variables which have more power in separating insolvent member countries from healthy countries. Then, bankruptcy of countries has been predicted using logistic regression in two models. Findings from research indicate that use of efficiency in bankruptcy prediction model increases model prediction accuracy.

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International Journal of Scientific Research in Science, Engineering and Technology

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Published

2017-12-31

Issue

Volume 3, Issue 8, November-December-2017

Section

Research Articles

License

Copyright (c) IJSRSET

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This work is licensed under a Creative Commons Attribution 4.0 International License.

How to Cite

[1]
Pedram Gharaei, " Presenting Effective way to Model Strategic Debt Recovery in World Trade : A Strategic Management Approach, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 3, Issue 8, pp.179-184, November-December-2017.